Master of Science in Decision Theory
The Master of Science in Decision Theory is an advanced program that delves into the principles of rational choice, probabilistic reasoning, and strategic decision-making across complex systems. This interdisciplinary program integrates cognitive science, game theory, behavioral decision models, and applied risk analysis to provide a comprehensive framework for understanding and optimizing decision processes. Students will engage with advanced decision models, probabilistic reasoning frameworks, and multi-agent systems, developing practical skills for applying these theories in real-world decision-making contexts. This program provides both a rigorous theoretical foundation and hands-on experience in applied decision analysis, preparing graduates for roles in research, strategy, and AI-driven decision systems.About the Program
The Master of Science in Decision Theory is designed for students seeking a deep understanding of decision-making processes and their applications in business strategy, policy analysis, and artificial intelligence. The program integrates classical decision theory with modern advances in cognitive science, behavioral economics, and probabilistic modeling to explore how decisions are made under uncertainty and how they can be optimized. Students will explore topics such as Bayesian inference, multi-criteria decision-making, and game theory, applying these concepts to real-world challenges. The program emphasizes both the theoretical and practical aspects of decision science, equipping students with the tools to analyze and design decision-support systems and improve strategic outcomes. Through a research-driven approach, students will develop advanced decision models, explore cognitive biases and ethical dilemmas, and design solutions for dynamic, multi-agent environments. The capstone research project allows students to apply their knowledge to a practical or theoretical decision-making problem, producing innovative solutions and frameworks.Key Areas of Study
- Rational Choice Theory and Utility Models
- Game Theory and Strategic Decision-Making
- Behavioral Decision Science and Cognitive Bias Analysis
- Probabilistic Reasoning and Bayesian Networks
- Risk Management and Ethical Decision-Making
Who Should Enroll?
This program is ideal for professionals, researchers, and AI specialists interested in decision science, behavioral modeling, and cognitive decision-making frameworks. Whether pursuing academic research or applied roles in strategic planning, AI systems, or public policy, this program provides the expertise needed to engage in advanced decision analysis and multi-agent system design.Core Curriculum & Program Structure
Program Courses: 33 credits
Degree Requirements
Total Credits Required: 33 credits
Core Major Courses: 24 credits
Research & Thesis: 9 credits
Year One – Foundations of Decision Science
Fall Semester 1
DET 501 – Foundations of Decision Theory (3 credits)
Introduction to fundamental concepts of decision theory, focusing on rational choice, utility theory, and decision-making under uncertainty.
DET 502 – Game Theory and Strategic Decision-Making (3 credits)
Exploration of game theory principles and their applications in strategic decision-making, negotiation, and competitive environments.
DET 503 – Behavioral Decision Theory (3 credits)
Study of how psychological and cognitive factors influence decision-making. Emphasis on heuristics, biases, and deviations from rational models.
Spring Semester 2
DET 504 – Probabilistic Reasoning and Bayesian Networks (3 credits)
Examination of probabilistic reasoning in decision-making processes, with a focus on Bayesian networks and probabilistic models of inference.
DET 505 – Decision Analysis and Risk Management (3 credits)
Application of decision analysis methods to risk management. Topics include multi-criteria decision analysis, sensitivity analysis, and uncertainty modeling.
DET 506 – Ethical Decision-Making in Complex Systems (3 credits)
Analysis of ethical considerations in decision-making across complex systems. Emphasis on moral frameworks, values-based decision-making, and ethical dilemmas in technology and policy.
Year Two – Specialized Research & Capstone
Fall Semester 3
DET 601 – Advanced Topics in Multi-Agent Decision Systems (3 credits)
Focus on multi-agent environments, cooperative strategies, and optimization in decentralized decision-making processes.
DET 602 – Independent Research in Decision Science (3 credits)
Individual research project guided by faculty, focusing on a specialized area of decision science.
DET 603 – Cognitive Models in Decision-Making (3 credits)
Advanced exploration of cognitive decision models, focusing on computational approaches to decision-making and human-machine collaboration.
Spring Semester 4
DET 699 – Capstone Thesis in Decision Theory (6 credits)
A culminating research project where students apply decision theory to a practical or theoretical problem. The capstone involves producing a comprehensive thesis that contributes to the field of decision science.